プロフィール詳細

プロジェクトを作成

★★★★★

☆☆☆☆☆

★★★★★

☆☆☆☆☆

Oscar G.に依頼

United States

Protein Engineering Specialist | Integrating Wet Lab Screening with Machine Learning & Data Analysis

プロフィール概要

I am a PhD researcher in Plant Biology specializing in Protein Engineering and Bioinformatics. My research focuses on using high-throughput wet-lab screens paired with machine learning to engineer immune proteins for enhanced crop immunity. This work has given me general expertise in designing "biologically aware" machine learning workflows, generating high-quality experimental data in the lab and using Python/R to model evolutionary trajectories, protein stability, and binding affinities. I help biotech and ag-tech teams solve problems where standard data analysis fails to account for biological complexity. Whether you need to design a robust high-throughput screen, analyze binding kinetics, or model variant effects, I offer a full-stack R&D approach. Core Services & Expertise: Computational Modeling & Machine Learning: - Variant Effect Prediction: Using ML algorithms to map evolutionary trajectories and predict how mutations influence protein stability and function. - Biophysical Modeling: Fitting experimental data to physical models (e.g., Hill-Langmuir equations, global epistasis models) to extract meaningful thermodynamic parameters. - Data Analysis: Using Python (Pandas, SciPy) and R (ggplot2) to clean, normalize, and visualize complex assay data for publication. High-Throughput Screening & Library Design: - Design and execution of Yeast Two-Hybrid (Y2H) and Yeast Surface Display screens. - Construction of mutagenized and combinatorial variant libraries for Deep Mutational Scanning (DMS) and Directed Evolution. - Optimization of screening protocols to minimize noise and maximize statistical power. Biophysical Characterization: - Quantitative binding affinity determination using Microscale Thermophoresis (MST) and Spectral Shift technology to validate screening hits. Technical Stack: - Languages: Python, R, Bash - Tools: PyMOL, ChimeraX, Jupyter Notebooks, RStudio - Lab Techniques: Molecular Cloning, Y2H, Yeast Surface Display, MST, PCR, Protein Expression I am passionate about solving the "right" problems. If you have a dataset that needs a biological interpretation or an experimental pipeline that needs optimization, let's connect.

専門分野

• ☆ Molecular Biology
• ☆ Genetics
• ☆ Biotechnology & Bioengineering
• ☆ Recombinant Protein Expression
• ☆ Agronomy & Crop Science
• ☆ Plant Biotechnology
• ☆ Data Analysis
• ☆ Machine Learning
• ☆ Synthetic Biology
• ☆ Agricultural Biotechnology
• ☆ Python

サービス

• Writing

Writing Technical Writing

職務経験

University of California, Davis

- 現在

Graduate Student Researcher

Univeristy of California, Davis

9月 2024 - 現在

Junior Specialist

University of California, Davis

8月 2023 - 9月 2024

学歴

Ph.D. Plant Biology

University of California, Davis

9月 2024 - 現在

B.Sc. Biology

Haverford College

8月 2019 - 5月 2023

認定資格

• Harvard CS50

  Harvard University

  https://certificates.cs50.io/60f0898f-3040-463f-9676-110358b03294.pdf?size=letter

  3月 2025 - 現在

出版物

JOURNAL ARTICLE

Oscar Garrett, Jonathan Berlingeri, Abelina Fuentes, Earl Ranario, Heesup Yun, Ellen Y. Rim, Alexander Howard, Mary-Francis LaPorte, Sassoum Lo, Duke Pauli, et al. (2025). Integration of crop modeling and sensing into molecular breeding for nutritional quality and stress tolerance . Theoretical and Applied Genetics.

Areta L N Bifendeh, Kenneth K Hsu, Christina M McBride, Charlie M Ferguson, Eva R Baumann, Diego Capcha-Rodriguez, Xinnuo Chen, Berlensie Chery, Margo M Chihade, Paola Delgado Umpierre, et al. (2024). Exploring the compatibility of phosphopantetheinyl transferases with acyl carrier proteins spanning type II polyketide synthase sequence space . Journal of Industrial Microbiology and Biotechnology.

Oscar Garrett, Kristen E. Whalen (2023). A bacterial quorum sensing signal is a potent inhibitor of de novo pyrimidine biosynthesis in the globally abundant Emiliania huxleyi . Frontiers in Microbiology.

PREPRINT

Alexander J. Howard, Ellen Y. Rim, Oscar D. Garrett, Yejin Shim, James H. Notwell, Pamela C. Ronald (2025). Combining Directed Evolution with Machine Learning Enables Accurate Genotype-to-Phenotype Predictions .

Ellen Y. Rim, Oscar D. Garrett, Alexander J. Howard, Yejin Shim, Yuanyuan Li, Jonathan E. Van Dyke, Ryan C. Packer, Nguyen Ho, Rashmi Jain, Valley Stewart, et al. (2024). Directed Evolution of a Plant Immune Receptor for Broad Spectrum Effector Recognition .